
SUMMARY_TENSORS = ['distort_image/image_with_bounding_boxes:0',
                        'distort_image/images_with_distorted_bounding_box:0',
                        'distort_image/final_distorted_image:0',
                        'distort_image_1/cropped_resized_image:0',
                        'Losses/cross_entry_loss:0',
                        'Losses/regularization_losses:0',
                        'distort_image_1/image_with_bounding_boxes:0',
                        'distort_image/cropped_resized_image:0',
                        'distort_image_1/images_with_distorted_bounding_box:0',
                        'distort_image_1/final_distorted_image:0',
                        'losses/aux_loss/value:0',
                        'losses/softmax_cross_entropy_loss/value:0',
                        'total_loss_1:0',
                        'learning_rate:0']


TRAIN_DIR = '../my-data/t/1/'

DATASETS_DIR = '../my-data/train'
VAL_DATASETS_DIR = '../my-data/val'
LABEL_PATH = '../labels.txt'
MODEL_NAME = 'inception_v4'


WEIGHT_DECAY = float(0.00004)

NUM_CLASSES = 3
NUM_TRAIN_SAMPLES = 40000
NUM_VAL_SAMPLES = 500


NUM_READERS = 8
NUM_PREPROCESSIN_THREADS = 4



BATCH_SIZE = 4
NUM_MAX_STEPS = 200000
LEARING_RATE = float(0.0001)
LEARNING_TYPE = 'fixed'  # 'exponential'
OPTIMIZER = 'momentum'   # 'sgd', 'adam', 'rmsprop', 'momentum'


NUM_EPOCHS_PER_DECAY = 30
lr_decay_factor = 0.95
SNAPSHOT = 1000
NUM_LOG_INTERVAL = 10
NUM_VAL_INTERVAL = 1000